Paul O'Leary

Comp 4433 - Data Visualizations

Project - Various plots of Alcohol Consumption and Wine Grape Production

My wife and I recently finished our basement, adding a well-stocked bar and a wine room. We both enjoy a nice glass of wine with dinner, and I like a glass of good whiskey or bourbon after a long week. I had previously looked at various Wine review datasets on Kaggle and other repositories, but after a number of searches, I discovered an extensive collection of data from the University of Adelaide in Australia.

The data is available here: https://economics.adelaide.edu.au/wine-economics/databases#database-of-regional-national-and-global-winegrape-bearing-areas-by-variety-1960-to-2016 and includes data from Australia and the world on various wine and beverage consumption topics.

Notes:

Initially, I looked at Wine, Beer and Spirits Consumption per capita. There are gaps in the data - most notably during Prohibition in the US and during World War 2, and there just is not data for many countries. However, I think the graphs still show some interesting trends.

What follows is a fair amount of cleanup to get the data into a usable form for Plotly Choropleths.

Some choropleths for 1964 and 2014.

In 1964, France, Portugal, Italy and Spain in Europe consumed by far the most wine. Somewhat surprising to me is that Argentina and Chile also were heavy wine consumers.

By 2014, France, Italy and Portugal still lead the way, but there consumption is less than half as much per capita than it was in 1964. Furthermore, the rest of the world has begun to catch up, notably Australia, UK and Germany.

Now, Animate the Wine map to show the changes over time. Much cleanup and testing to get the data ready for that.

The first attempt below is obviously missing something!

I need the country codes in the data to feed to the choropleth!

There's a number of non-country listings in the data - need to be cleaned up.

Much better!

Below, I create another figure without the title for use in DASH.

Let's look at beer!

I'll try to consolidate the individual steps from above to compact it.

Not really a surprise, but Germany, Australia and the UK led the way with beer consumption in 1964, followed closely by North America.

By 2014, beer is much more widely consumed.

Now a glimpse into Spirits Consumption

I was somewhat surprised to see Russia leading the way in Spirits consumption.

Bulgaria and Thailand nudge out Russia for cunsumption of spirits.

Below is the first attempts to get DASH to work. Commented out right now.

The following attempt at using DASH works!

Again, as noted, I used the interactive JupyterDash, and there was no way to save just the HTML. DASH uses javascript extensively and does not include the data in the HTML pieces.

I decided to look at Wine grape growth by Country by Hectare. Who grows the most red and white grapes globally? For now, data is just for 2016.

Probably not surprisingly, France, Spain and Italy lead the way in red grape production, with production in the US, China and Argentina running at about half as much.

Spain leads the way for white grape growth in hectares. For the record, a "hectare" is approximately 2.5 acres.

Here, I began playing with types of red grapes, and where they are grown.

This data is probably best represented by pie charts, since it is only 20 countries.

Below begins various attempts to get a drop down list of grape types to display the pie charts.

Trouble getting the above to work. Let me try a work around, to create all the pie charts, then pull them in to DASH.

This was a brute force attempt that got a little closer.

Here, I am trrying to figure out a way to work around the DASH issue, like I did above.

In the above, the selection works, but it ADDS the next selection to the display, rather than overwriting the previous.

THANKS!!